**Other Locations:** United States-New York-Tarrytown, United States-New Jersey-Flanders, United States-Pennsylvania-Malvern, United States-North Carolina-Cary, United States-Washington-Spokane, United States-Illinois-Hoffman Estates

**Assignment Category:** Full-time regular

**Experience Level:** Senior level

**Education Required Level:** Master's Degree

**Travel Required:** 20%

**Division Description:**

Siemens is a global technology powerhouse that has stood for engineering excellence, innovation, quality, reliability and internationality for more than 165 years. As a global technology company, Siemens is rigorously leveraging the advantages that this setup provides. To tap business opportunities in both new and established markets, the Company is organized in nine Divisions: Power and Gas, Wind Power and Renewables, Energy Management, Building Technologies, Mobility, Digital Factory, Process Industries and Drives, Healthineers and Financial Services.

With 45,000 employees Siemens Healthineers is one of the worlds largest suppliers of technology to the healthcare industry and a leader in medical imaging, laboratory diagnostics and healthcare IT. All supported by a comprehensive portfolio of clinical consulting, training, and services available across the globe and tailored to customers needs. So that more people can have a life that is longer, richer, and more filled with happiness.

For more information, please visit: http://www.usa.siemens.com/healthineers

**Job Description:**

**This position is responsible for leading a team of talented data scientist and analyst for multiple next generations of PHM healthcare application and platform using the latest cloud technologies for large scale enterprise application.**

Responsibilities:

Create frameworks in which data science can be performed, managed, and tracked for multiple projects

Manage multiple projects with a team of talented data scientists, analyst, engineers and project managers

Mentor and train a team of data scientists and analysts

Define and drive requirements for adapters to enterprise data sources, a data warehouse to receive and organize the data

Close collaboration with data engineers to ensure availability of data

Create and implement algorithms to process healthcare data for descriptive and predictive analytics to extract meaning from large scale structured and unstructured health data